{"id":"W4353100331","doi":"10.18280/ts.400106","title":"DM-EEGID: EEG-Based Biometric Authentication System Using Hybrid Attention-Based LSTM and MLP Algorithm","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biometrics; Computer science; Authentication (law); Speech recognition; Artificial intelligence; Electroencephalography; Pattern recognition (psychology); Algorithm; Computer security; Psychology; Neuroscience","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002874926,0.0004702624,0.0004189846,0.0003515289,0.0002147575,0.0003717368,0.0006753625,0.0004690615,0.002207096],"category_scores_gemma":[0.0004491859,0.0001513002,0.0002989917,0.0002929483,0.0001335807,0.0005328399,0.0005983242,0.0004989756,0.0006746346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003496957,"about_ca_system_score_gemma":0.0003031797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002687647,"about_ca_topic_score_gemma":0.003398598,"domain_scores_codex":[0.9998145,0.0000208364,0.00001242905,0.00006778857,0.00005698818,0.0000276079],"domain_scores_gemma":[0.9999024,0.00001822863,0.00001219945,0.00001166341,0.00004610136,0.00000942455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007282664,0.0002393348,0.003299162,0.0002991163,0.000167284,0.0003171438,0.00009352253,0.02130872,0.1447251,0.001064586,0.008262439,0.8194952],"study_design_scores_gemma":[0.00009354457,0.0006193238,0.01504587,0.00006878861,0.0001572573,0.0009576599,0.0000486286,0.8935508,0.07965803,0.001408006,0.008319317,0.00007279994],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.130582,0.002234147,0.8489961,0.0004784339,0.0003933681,0.000213609,0.0009939574,0.009219293,0.006889034],"genre_scores_gemma":[0.821616,0.0007245166,0.165555,0.0004193269,0.0001260385,0.0002083589,0.001266281,0.00006544972,0.01001901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002687647,"threshold_uncertainty_score":0.007383466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0412407003857865,"score_gpt":0.2755566169271517,"score_spread":0.2343159165413652,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}